Job Description

As an Applied Research intern at Labelbox, you will design, build, and productionize evaluation and post‑training systems for frontier LLMs and multimodal models. You’ll own continuous, high-quality evals and benchmarks, create and curate post‑training datasets, and prototype training loops to measure and improve real‑world task and agent performance.

Responsibilities

• Build and own evaluation and benchmark suites
• Create post‑training datasets at scale
• Experiment and prototype training loops
• Land research in product
• Engage with customer research teams

Requirements

• Strong foundation in AI and machine learning with a relevant degree
• Deep understanding of frontier autoregressive and diffusion multimodal models
• Passion and experience for LLM evaluation and benchmarking
• Expertise in training data quality construction, measurement and refinement
• Ability to bridge research and application
• Track record of publishing in top-tier AI/ML conferences
• Proficiency in Python and experience with deep learning frameworks
• Exceptional communication and collaboration skills

Benefits

• No benefits